Kelli Bramlett

High throughput expression profiling and in situ screening of circular RNAs in tissues

Circular RNAs (circRNAs) were recently discovered as a class of widely expressed noncoding RNA and have been implicated in regulation of gene expression. However, the function of the majority of circRNAs remains unknown. Studies of circRNAs have been hampered by a lack of essential approaches for detection, quantification and visualization. We therefore developed a target-enrichment sequencing method suitable for high-throughput screening of circRNAs and their linear counterparts. We also applied padlock probes and in situ sequencing to visualize and determine circRNAs localization in human brain tissue at subcellular levels. We measured circRNA abundance across different human samples and tissues. Our results demonstrate the potential of this RNA class to act as a specific diagnostic marker in blood and serum, by detection of circRNAs from genes exclusively expressed in the brain. The powerful and scalable tools we present will enable studies of circRNA function and facilitate screening of circRNA as diagnostic biomarkers.

Abstract 5396: An NGS workflow to detect down to 0.1% allelic frequency in cfDNA for breast and colon cancers

Noninvasive detection of rare mutations in blood could allow tumor monitoring for research purposes. Research studies have suggested that cfDNA contains DNA from tumor cells with somatic mutations that could inform on tumor progression and therapeutic resistance. Here, we demonstrate a complete workflow from a single tube of blood through data analysis for research samples down to a 0.1% allelic frequency. The low abundance tumor mutations found in cfDNA requires sensitive and accurate mutation detection. We have developed two panels that utilize an amplification-based assay that generates tagged DNA copies, which allows detection of low abundance tumor mutations found in cfDNA. The two panels allow multiplex interrogation of primary driver and resistance mutations specific to ctDNA from breast and colon cancer. The Oncomine Colon cfDNA panel targets 236 hotspots within 14 genes while the Oncomine Breast cfDNA panel covers 157 hotspot mutations in 10 genes. This workflow was validated from matched single blood tubes, Streck and K2EDTA. Additionally, the utility for cancer research was demonstrated with concordance studies using matched FFPE and plasma from oncology samples. To further characterize these panels we have developed an oncology control for cfDNA with nucleosome fragment sizing and minimal sonication damage. This engineered control contains SNPs and indels at 0.1% allelic frequencies, orthogonally confirmed with TaqMan based Rare Mutation assays. With this control, the Oncomine Breast cfDNA panel had over 81% sensitivity and 99.9% specificity. The Oncomine Colon cfDNA panel had over 85% sensitivity and 100% specificity. The Oncomine Breast cfDNA panel and Oncomine Colon cfDNA panel integrated into a complete workflow starting from a single tube of blood can advance oncology research with the ability to detect blood based cancer biomarkers present at 0.1%. Citation Format: Dalia Dhingra, Richard Chien, Jian Gu, Dumitru Brinza, Ruchi Chaudhary, Kunal Banjara, Yanchun Li, Efren Ballesteros-Villagrana, Kelli Bramlett. An NGS workflow to detect down to 0.1% allelic frequency in cfDNA for breast and colon cancers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 5396. doi:10.1158/1538-7445.AM2017-5396

Abstract 3622: Complete workflow for detection of low frequency somatic mutations from cell-free DNA using Ion Torrent™ platforms

Research detecting of somatic mutations in circulating cell-free DNA (cfDNA) using research blood samples from subjects previously diagnosed with cancer provides a potential non-invasive approach to monitor cancer status and evaluate cancer evolution in the future. However, most of the existing mutation detection methods show insufficient sensitivity to detect cfDNA mutations since only small amount of mutant gene fragments, derived from tumor cells, is present in a large amount of normal circulating DNA background. We demonstrated a complete workflow that includes blood collection, cfDNA isolation, library preparation, sequencing, and data analysis to enable detection of rare DNA variants in blood plasma samples. Blood samples were collected using Streck™ DNA tubes followed by plasma preparation and cfDNA isolation using MagMAX™ Cell-Free DNA Isolation Kit. Library preparation was performed using Oncomine™ lung cfDNA kit. Barcoded libraries were pooled and sequenced on Ion Torrent™ Next Generation Sequencing Platforms. Sequencing data was analyzed in Torrent Suite™ using variantCaller-cfDNA plugin. ∼150 biomarkers relevant to non-small cell lung cancer were interrogated in one sequencing run. We demonstrated detection sensitivity at 0.1% frequency using engineered mutants that were spiked into control DNA samples. The workflow was tested on a set of research samples from matched tumor FFPE and blood plasma collected from research subjects with non-small cell lung cancer (NSCLC). About 1 mL of plasma was processed using the workflow described above. RecoverAll™ Multi-Sample RNA/DNA Isolation Workflow was used to isolate DNA from FFPE samples, followed by library preparation, sequencing and data analysis using the same workflow described above. Summary of variant calls from matched cfDNA and FFPE tumor samples are presented here. Results indicate high sensitivity of the workflow and expected levels of concordance between variants detected in the two types of research samples. In this study, we developed a highly sensitive and reliable research workflow to detect rare somatic mutations in circulating cfDNA samples. Significant overlapping of mutations discovered in FFPE tumor and cfDNA samples suggests that this workflow may be used to monitor tumor dynamics in NSCLC and potentially other tumors in the future. Disclaimer: For research use only. Not for use in diagnostic procedures. Citation Format: Jian Gu, Dumitru Brinza, Ann Mongan, Richard Chien, Dalia Dhingra, Fiona Hyland, Kelli Bramlett. Complete workflow for detection of low frequency somatic mutations from cell-free DNA using Ion Torrent™ platforms. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 3622.

Abstract 1386: Clinical research results for a NGS-based kit for targeted detection of clinically relevant gene rearrangements in lung tumor samples

In recent years, advances in next-generation sequencing (NGS) technologies have enabled faster and cheaper methods for uncovering the genetic basis of disease. For cancer, NGS based screening for known tumor subtypes may inform diagnosis and allow the clinician to tailor a specific therapeutic approach in the future. Here, we present the testing results of one such NGS based kit used to detect specific chromosomal translocations in retrospective non-small cell lung cancer (NSCLC) samples by targeting specific breakpoints in known fusion transcripts. The included panel tested consists of a single primer pool containing amplicon designs to simultaneously screen for over 75 specific rearrangements involving the receptor tyrosine kinase (RTK) genes ALK, RET and ROS1 as well as NTRK1. The panel was compatible with formalin-fixed paraffin-embedded (FFPE) lung tumor research samples and achieved high-sensitivity down to 10 ng of RNA input. In addition, amplicon assays designed at the 5’ and 3’ ends the RTK genes provide non-specific evidence that a translocation exists in a sample by comparing expression imbalance between the two ends. Testing was carried out at three external clinical research laboratories. In addition to positive and negative control samples, each site contributed FFPE lung tumor research samples for which ALK fusion status was known prior to NGS library preparation carried out using the Ion AmpliSeq™ workflow. For site-specific samples (n = 144, 16 samples per sequencing run), high concordance, sensitivity and specificity were measured at 97.2%, 90.5% and 98.4%, respectively. Citation Format: Jeoffrey J. Schageman, Jose Luis Costa, Orla Sheils, John E. Glassco, David Chi, Jon Sherlock, John Bishop, Rosella P. Petraroli, Kelli S. Bramlett. Clinical research results for a NGS-based kit for targeted detection of clinically relevant gene rearrangements in lung tumor samples. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 1386.

Abstract 5272: Cloud-based informatics enables the design and analysis of massively multiplex custom gene fusion panels for next-generation sequencing on FFPE RNA samples

Gene fusions, a combination of two genes, comprising their coding and/or regulatory sequences, are caused by structural rearrangements in DNA or in RNA transcripts. Many gene fusions are strong driver mutations in neoplasia, and are important in understanding basic biology, interaction with targeted therapy, and research into risk stratification and outcomes. Next-generation sequencing enables sensitive, specific and precise detection of particular fusion isoforms for defined gene pairs. Massively multiplex Ampliseq gene fusion assays enable enrichment of fusion transcripts using as little as 10 ng of RNA extracted from FFPE samples. Sequencing on Ion Torrent instruments reveals the full sequence of the gene fusion, for precise definition of the breakpoint and the expressed exons or promoter regions of both genes. We developed cloud-based software to support the design of a custom Ampliseq gene fusion panel, comprising 1 to 1,000 fusion isoform assays and any gene expression assays for normalization. We extensively mined the scientific literature on fusions and the COSMIC database to identify over 1000 fusion isoforms. We rigorously curated this data using automated and manual methods, including mapping, confirmation and correction of reported sequence to obtain genomic coordinates, identification of breakpoints, annotation of exon junctions, and selected wet lab testing. We created a database containing over 1000 high quality curated and annotated fusion isoforms, including 70 ALK, 60 RET, 26 ROS1, and 21 NTRK1 fusions. We designed Ampliseq primer pairs for each of these fusions using advanced assay design and pooling algorithms, such that all fusion and gene expression assays can be multiplexed into 1 or 2 compatible pools. Assays can be selected by gene or gene pair; detailed information about each assay selected includes isoform, genes, exon numbers, and links to COSMIC and to relevant publications. We developed cloud-based analysis software to analyze the BAM file resulting from amplification and sequencing of custom Ampliseq fusion panels on an Ion Torrent sequencer. This analysis leverages the rich annotation information from the assay design. The reads are mapped to a custom reference sequence tailored to the custom Ampliseq fusion assay, and applying an optimized algorithm to select confidently mapped reads based on read length and overlap with each gene of the gene pair based on the reference and annotated breakpoint. Gene fusions are detected based on the total number of fusion reads and optionally frequency, and on the properties of those reads. Software QC steps for total number of mapped reads, number of reads for gene expression controls, and elimination of cross-talk artifacts result in a highly sensitive and specific detection of fusions, with LOD below 1%. Fusion results for any or all samples can be viewed, annotated, filtered, and visualized, and exported. Citation Format: Fiona Hyland, Rajesh Gottimukkala, Efren Ballesteros, Heinz Breu, Yuandan Lou, Scott Myrand, Michael Hogan, Kelli Bramlett, Guoying Liu, Seth Sadis. Cloud-based informatics enables the design and analysis of massively multiplex custom gene fusion panels for next-generation sequencing on FFPE RNA samples. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 5272.

Abstract 5267: Gene fusion database to create custom panels: Enabling detection of fusion transcripts and gene expression assays

Gene fusions play an important role in tumorigenesis and are increasingly recognized as important entities for the diagnosis and treatment of hematological malignancies and solid tumors. Fusion events generate a hybrid mRNA transcript comprising sequence from multiple otherwise distinct genes. Oncogenic fusion events often involve tyrosine kinases or transcription factors, leading to aberrant growth signaling, making these events potentially attractive drug targets. For instance, targeted therapies such as known tyrosine kinase inhibitors are currently approved to treat ALK fusion positive Non-Small Cell Lung Carcinoma (NSCLC) patients. Detection of known gene fusion events is an important part of genomic characterization which can inform patient diagnosis. Current methods for fusion detection include chromosome banding analysis (CBA), fluorescence in situ hybridization (FISH), and reverse transcription polymerase chain reaction (RT-PCR). New developments in next-generation sequencing (NGS) enable the efficient and simultaneous assessment of multiple gene fusion targets with high sensitivity. To enable researchers to design their own custom panels and assess a set of gene fusions of interest, we developed a comprehensive RNA gene fusion database. Oncology researchers now have the capability to create custom panels from this comprehensive database which includes over 1,000 well annotated and optimized gene fusion assays and over 20,000 gene expressions assays. To build this comprehensive gene fusion database, we identified breakpoint information for 1,178 well annotated fusions described in publications and in the COSMIC and NCBI databases. We prepared a target RNA sequence for each breakpoint using transcript sequences from the Ensembl database. We used a proprietary primer designer to generate candidates for each fusion target amenable to the AmpliSeq™ product line requirements. Quality control was performed throughout the design process to identify the best primer set for each target, to avoid primers overlapping common germline SNPs, potential primer/primer or primer/amplicon interactions, or off-target or wild-type amplifications. With this comprehensive database we provide a complete range of solutions available on ampliseq.com. Making use of the AmpliSeq™ technology, researchers now have the capability to create their own custom fusion panel and place the order within an hour. These custom panels are used with AmpliSeq™ Library reagents and Ion Torrent™ sequencing platforms for targeting next-generation sequencing. The analysis solution is provided through the Ion Reporter™ (IR) software package. Custom fusion panel workflows in IR are used to analyze sequencing data coming from the custom panels, which includes visualization of fusion transcripts and gene expression levels in a heat map feature. Citation Format: Efren Ballesteros-Villagrana, Jeoffrey Schageman, Kelli Bramlett, Paul Williams, Scott Myrand, Guoying Liu, Fiona Hyland, Seth Sadis. Gene fusion database to create custom panels: Enabling detection of fusion transcripts and gene expression assays. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 5267.

Abstract 1836: Global gene expression profiles from bladder tumor FFPE samples

Cancer is a disease characterized by uncontrolled cell growth and proliferation. Recent advances in molecular medicine and cancer biology have changed the way clinicians evaluate and consider treatment. Selected tumor biomarkers have been utilized as targets for drug therapy leading to better more effective treatment. Gene expression profiling has been used for identifying new biomarkers for tumor classification and driving decision making for better patient outcome in different tumor types. DNA microarrays have become a key method to acquire a comparative snapshot of the gene expression profile from test samples in a high throughput manner. Quantitative PCR and newer sequencing techniques are popular alternatives offering highly accurate gene expression measurements, but with limitations due to cost, complex instrumentation and analysis needs. RNA extracted from formalin fixed paraffin embedded tissue (FFPE) creates considerable additional challenges in acquiring accurate gene expression measurements due to the highly fragmented and compromised integrity of FFPE RNA due to the fixation process. To address the challenges of current sequencing based methods and take advantage of the simplicity of analysis that comes with using technologies such as microarrays; we have tested the Ion AmpliSeq™ Transcriptome Human Gene Expression Kit using RNA isolated from bladder tumor FFPE specimens. This targeted RNA sequencing approach allows profiling the global mRNA expression of human RNA in a highly multiplexed fashion using the Ion AmpliSeq™ technology. 10ng of total RNA extracted from FFPE tissue was reverse transcribed followed by automated library preparation on the Ion Chef™ system using the new Ion AmpliSeq™ Kit for Chef and the Ion AmpliSeq™ Transcriptome Human Gene Expression Panel. Eight pooled libraries were then sequenced on the Ion S5™XL System with Ion 540™ Chip. Libraries were also prepared with well characterized control RNAs, Universal Human Reference RNA (UHR) and First Choice Human Brain Reference RNA (HBR) using both the manual and automated library generation protocol for validation and comparison studies. The results show detection of more genes than popular microarray platforms with comparable differential gene expression measurements to quantitative PCR (r = 0.96) and RNA-Seq methods (r = 0.94). Gene expression values correlated with R>0.99 for all technical replicates and R>0.95 between manual and automated library preparation methods using well characterized samples. The Ion AmpliSeq™ Transcriptome Human Gene Expression Kit is a simple method to measure global gene expression profiles from human RNA samples in a timely, cost effective, and high throughput manner resulting in sensitive and accurate gene expression measurements. The new S5™XL System combined with automated library and template preparation on the Ion Chef™ system enable a simple RNA to gene expression data workflow requiring only 45 minutes of hands on time from 10ng of FFPE RNA. Citation Format: Varun Bagai, Jeoffrey Schageman, Kelli Bramlett, David J. McConkey, Woonyoung Choi. Global gene expression profiles from bladder tumor FFPE samples. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 1836.

Abstract 3959: Detection of somatic mutations at 0.1% frequency from cfDNA in peripheral blood with a multiplex next-generation sequencing assay

Background: Effective blood screening for tracking of recurrence and resistance of tumors may improve outcomes in the future. Research studies suggest that virtually all tumors carry somatic DNA mutations, and these may serve as biomarkers that also can be tracked in blood. One of the sources containing tumor DNA in blood is circulating cell-free DNA (cfDNA). Tumor DNA comes from different tumor clones, and its abundance in plasma can be very low at critical stages such as early recurrence or development of resistance. Hence, there is great interest in being able to detect mutation biomarkers at very low frequency from cfDNA for detection and characterization of tumor clones. Method: We present a research use only analysis workflow for peripheral monitoring that enables detection of low frequency DNA variants in blood. We developed an analysis algorithm that models errors accumulated during amplification and sequencing, and accurately reconstructs sequence of original DNA molecules based on multiple next generation sequencing reads. The reads contain genomic sequence and an adaptor that allows identification of reads originated from the same DNA molecule. We then developed a variant calling method that uses accurately reconstructed sequences to enable sensitive and specific detection of somatic mutations to 0.1% allele ratio. We demonstrate the analysis in control and archived cfDNA research samples. We used a next generation sequencing assay that allows interrogation of ∼150 biomarkers relevant in lung from COSMIC and Oncomine™ databases, and de-novo variant detection at ∼1,700 genomic positions in 11 genes implicated in non-small cell lung cancer (NSCLC).The assay delivers >95% on target reads and highly uniform amplification across targeted cfDNA molecules. Results: We tested the limits of variant detection in controlled dilution series and in cfDNA. First, we diluted engineered AcroMetrix™ Oncology Hotspot Control plasmids into background GM24385 genomic DNA down to 0.1% frequency, and then fragmented into fragments with average size of 170bp. The Acrometrix sample contains ∼45 common tumor mutations interrogated by our assay. Next, we used 0.1% Horizon9s (HD780) cfDNA reference sample that contains 8 mutations at our hotspot positions including two large insertion and deletion variants of size >10bp. Finally, we performed analytical verification of variant detection performance in cfDNA using a dilution series of normal blood samples. We achieved >95% sensitivity with >20ng input DNA and >90% sensitivity with ∼20ng input DNA and Conclusions: This new lung cfDNA analysis workflow may facilitate researchers to study relevant NSCLC biomarkers at 0.1% frequency in cfDNA. Analysis is compatible with lower frequency variant detection, but will require higher input DNA amount and higher sequencing coverage. Citation Format: Dumitru Brinza, Ann Mongan, Richard Chen, Dalia Dhingra, Jian Gu, Janice Au-Young, Fiona Hyland, Kelli Bramlett. Detection of somatic mutations at 0.1% frequency from cfDNA in peripheral blood with a multiplex next-generation sequencing assay. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 3959.

Abstract P4-07-09: Breast cancer specific expression of miRNA deciphered using next generation sequencing of LCM procured cells

The objective of this study is to decipher miRNA expression profiles of laser capture microdissection (LCM)-procured carcinoma cells compared to those of intact serial sections of a breast cancer biopsy. Our hypothesis is that miRNA signatures discerned from specific carcinoma cell populations more precisely correlate with clinical behavior than that provided by conventional biomarkers of intact tissue biopsies. De-identified frozen biopsies of invasive ductal carcinomas of known grade and biomarker status containing 35-70% cancer were selected from an IRB-approved Biorepository (JLW). Serial tissue sections were stained with H & E and 12-15,000 carcinoma cells were collected from an adjacent section. RNA was extracted using PureLink RNA Mini Kit™ (Invitrogen), evaluated (Agilent Bioanalyzer) and sequenced for miRNA expression using the Ion Torrent™ System (Thermo Fisher). Total RNAs were enriched for small RNA species using mirVana miRNA™ kits (Thermo Fisher) and RNA libraries were constructed from 5 ng of enriched RNA using Ion Total RNA-Seq Kit v2. Barcodes were utilized to multiplex libraries for template preparation and sequencing on Proton PI™ chips as twelve-plex library pools. Each library was sequenced to an average of 30M reads on the Ion Proton™sequencer with the Ion PI™ chip. Sequence reads were aligned to miRNA precursor hairpins available from the miRBase (miRBase.org) miRNA repository. Aligned reads to each miRBase reference miRNA were then reported. Using the R statistical software package, DESeq (Bioconductor), counts for all libraries were normalized and relative expression was calculated. Mapping statistics (e.g., aligned reads (range 59-79%) and miRBase matches (range 69-85%)) were assessed for each library. Comparison of expressed miRNAs from intact tissue sections with those of cognate carcinoma cells procured by LCM revealed, in general, that smaller defined miRNA gene sets were expressed in isolated populations of carcinoma cells. miRNA expression patterns of experimental pairs (intact vs LCM-procured) using MA-plots were highly variable in carcinomas with different grades, suggesting a relationship to disease status. Gene frequency plots, comparing expression from intact tissue sections to that of LCM-procured cell population, revealed subsets of differently expressed miRNAs. To increase statistical power, a follow-up experiment was performed with triplicate libraries from 4 different representative carcinoma samples. In addition to miRNA sequencing, targeted RNA sequencing with an Ion AmpliSeq™ RNA panel was used to capture gene expression information from the12 additional samples. From these replicated libraries, we are able to combine mRNA and miRNA expression information to create an expected profile from these breast carcinoma tissue samples. Application of Next Generation Sequencing of miRNAs and Ion AmpliSeq™ RNA panels using LCM-procured cells and intact tissue provides an innovative approach for assessing differential expression of miRNA and mRNA levels involved in breast cancer behavior. Supported in part by a grant from the Phi Beta Psi Charity Trust (JLW & SAA) and a CTSP Award from the Commonwealth of Kentucky (JLW). For research use only. Citation Format: Kelli S Bramlett, James L Wittliff, Jose G Cienfuegos, Sarah A Andres, Jeoffrey J Schageman. Breast cancer specific expression of miRNA deciphered using next generation sequencing of LCM procured cells [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr P4-07-09.